An Adaptive Network Model to Simulate Consensus Formation Driven by Social Identity Recognition

Joint Authors

Zhang, Kaiqi
Lv, Zinan
Du, Hai Feng
Zou, Honghui

Source

Complexity

Issue

Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-13, 13 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2020-10-08

Country of Publication

Egypt

No. of Pages

13

Main Subjects

Philosophy

Abstract EN

Models of the consensus of the individual state in social systems have been the subject of recent research studies in the physics literature.

We investigate how network structures coevolve with the individual state under the framework of social identity theory.

Also, we propose an adaptive network model to achieve state consensus or local structural adjustment of individuals by evaluating the homogeneity among them.

Specifically, the similarity threshold significantly affects the evolution of the network with different initial conditions, and thus there emerges obvious community structure and polarization.

More importantly, there exists a critical point of phase transition, at which the network may evolve into a significant community structure and state-consistent group.

American Psychological Association (APA)

Zhang, Kaiqi& Lv, Zinan& Du, Hai Feng& Zou, Honghui. 2020. An Adaptive Network Model to Simulate Consensus Formation Driven by Social Identity Recognition. Complexity،Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1139952

Modern Language Association (MLA)

Zhang, Kaiqi…[et al.]. An Adaptive Network Model to Simulate Consensus Formation Driven by Social Identity Recognition. Complexity No. 2020 (2020), pp.1-13.
https://search.emarefa.net/detail/BIM-1139952

American Medical Association (AMA)

Zhang, Kaiqi& Lv, Zinan& Du, Hai Feng& Zou, Honghui. An Adaptive Network Model to Simulate Consensus Formation Driven by Social Identity Recognition. Complexity. 2020. Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1139952

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1139952